Critical Motion Detection of Nearby Moving Vehicles in a Vision-Based Driver-Assistance System

Abstract

Abstract-Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized. A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system.Index Terms-Assembly of adaptive-resonance-theory (ART) neural networks, driver-assistance system (DAS), dynamic visual model (DVM), fuzzy integral, spatiotemporal attention (STA) neural network.

Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis

“…Dynamic modeling of the scene background in the area of the image where vehicles typically overtake was implemented in [77]. A similar concept, i.e., dynamic visual maps, was developed in [88] for detecting vehicles and identifying unusual maneuvering in the scene. In [89], a homography matrix was computed between adjacent video frames; image regions that did not cleanly map between frames were assumed to be vehicles.…”

“…Certain studies try to categorize observed vehicle behavior as normal or abnormal [88], identifying and highlighting critical situations. Other studies try to identify specific maneuvers, such as overtaking [164], turning [3], or lane changes [6].…”

“…In [3], the context of interest is intersections, i.e., the turning behavior of oncoming vehicles inferred. In [88], a dynamic visual model is developed of the driving environment, with saliency alerting the system to unusual and critical on-road situations.…”

Unusual Motion Detection for Vision-Based Driver Assistance

“…It is a common human experience of getting out of the way of a quickly moving object before actually identifying what it is [1]. In conclusion, a human can perceive motion earlier than form and meaning.…”

“…Driver-assistance systems (DASs) aim at bringing potentially hazardous conditions to the driver's attention in real time [1], and they also aim at more driver comfort. Autonomous driving is also already reality in on-road vehicles [2].…”